• Transactions of the Korean Society of Automotive Engineers
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• v.24 no.3
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• pp.265-272
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• 2016

The objective of vehicle aerodynamic design is on the fuel economy, reduction of the harmful emission, minimizing the vibration and noise and the driving stability of the vehicle. Especially for a sedan, the driving stability of the vehicle is the main concern of the aerodynamic design of the vehicle indeed. In this theoretical study, an evaluation algorithm of aerodynamic driving stability of a vehicle was made to estimate the dynamic stability of a vehicle at the given driving condition on a road. For the stability evaluation of a driving vehicle, CFD simulation was conducted to have the rolling, pitching and yawing moments of a model vehicle and compared the values of the moments to the resistance moments. From the case study, it is found that a model sedan running at 100 km/h in speed on a straight level road is stable under the side wind with 45 m/s in speed. But the different results may be obtained on the buses and trucks because those vehicles have the wide side area. From the case study of the model vehicle moving on 100 km/h speed with 15 m/s side wind is evaluated using the numerical algorithm drawn from the study, the value of yawing moment is $608.6N{\cdot}m$, rolling moment $-641N{\cdot}m$ and pitching moment $3.9N{\cdot}m$. These values are smaller than each value of rotational resistance moment the model vehicle has, and therefore, the model vehicle's driving stability is guaranteed when driving 100 km/h with 15 m/s side wind.

• Journal of Korean Society of Transportation
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• v.25 no.5
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• pp.149-160
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• 2007

Automobile black boxes store and provide accident and driving information. The accident and driving information can be utilized to build scientific traffic-event database and can be applied in various industries. The objective of this study is to develop a recognition system of dangerous driving through analyzing the driving characteristic patterns. In this paper, possible dangerous driving models are classified into four models on the basis of vehicle behaviors(acceleration, deceleration, rotation) and accident types from existing statistical data. Dangerous driving data have been acquired through vehicle tests using automobile black boxes. Characteristics of driving patterns have been analyzed in order to classify dangerous driving models. For the recognition of dangerous driving, this study selected critical value of each dangerous driving model and developed the recognition algorithm of dangerous driving. The study has been verified by the application of recognition algorithm of dangerous driving and vehicle tests using automobile black boxes. The presented recognition methods of dangerous driving can be used for on-line/off-line management of drivers and vehicles.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.341-343
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• 1995

In this paper, an algorithm is presented to recogniz the driving direction of a vehicle and obstacles in front of it based on highway road image. The algorithm employs a neural network with 27 sub sets obtained from the road image as its input. The outputs include the direction of the vehicle movement and presence or absence of obstacles. The road image, obtained by a video camera, was digitized and processed by a personal computer equipped with an image processing board.

• Journal of applied mathematics & informatics
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• v.30 no.1_2
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• pp.1-14
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• 2012

In this paper, the problem of determining the optimal car-deriving strategy has been examined. In order to find the optimal driving strategy, we have modified a method based on measure theory. Further, we demonstrate that the modified method is an efficient and practical algorithm for dealing with optimal control problems in a canonical formulation.

• Journal of Mechanical Science and Technology
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• v.19 no.5
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• pp.1107-1115
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• 2005

In this study, a position and force simultaneous trajectory tracking control algorithm is proposed for a driving apparatus that consists of two pneumatic cylinders connected in series. The controller applied to the driving apparatus is composed of a non-interaction controller to compensate for interaction between cylinders and a disturbance observer aimed to reduce the effect of model discrepancy that cannot be compensated by the non-interaction controller. The effectiveness of the proposed control algorithm is proved by experimental results.

• CDE review
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• v.21 no.2
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• pp.34-38
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• 2015

In case of the big city, choosing the adequate root of which we can reach the destination can affect the driver's condition and driving time. so it is quite important to find the optimal routes for arriving the destination as considering the factors, such as driving conditions or travel time and so on. In this paper, we develop route choice model with considering driving conditions and travel time, and it can search the optimal path which make drivers reduce their fatigues using genetic algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.173-178
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• 1998

The strategy presented in this paper is based on modifying the past patterens and adjusting the content of the driving patterns by a new algorithm. Learning happens during the driving procedure of a mobile vehicle. The purpose of this paper is to solve the problem how to realize the hardware neurocomputer by back propagation (BP) neural network learning on-line.

• Proceedings of the KIEE Conference
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• summer
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• pp.932-934
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• 2004

BLDC Motor is used in robots requiring a precisive motion recently. This paper presents the optimal design reducing the rotor inertia in order to improve the driving characteristic of BLDC motor driving robots, The optimal design was performed by using a parallel Genetic Algorithm which is superior at searching objective functions for the comflicated models having several optimal points. Therefore, objective function for optimization is rotor inertia and efficiency.

• Journal of Power System Engineering
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• v.10 no.3
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• pp.97-103
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• 2006

In this study, a position trajectory tracking control algorithm is proposed for a pneumatic artificial muscle driving apparatus composed of a actuator which imitates the muscle of human, a position sensor and a control valve. The controller applied to the driving apparatus is composed of a state feedback controller and disturbance observer. The feedback controller which feeds back position, velocity and acceleration is derived from the linear model of pneumatic artificial muscle driving apparatus. The disturbance observer is designed to improve trajectory tracking performance and to reduce the effect of model discrepancy. The effectiveness of the designed controller is proved by experiments and the experimental results show that the pneumatic artificial muscle driving apparatus with the proposed control algorithm tracks given position reference inputs accurately.

• Transactions of the Korean Society of Automotive Engineers
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• v.14 no.3
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• pp.28-34
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• 2006

An ACC driving simulator is a virtual reality device which designed to test or evaluate vehicle control algorithm. It is designed and built based on the rapid control prototyping(RCP) concept. Therefore this simulator adopt RCP tools to solve the equation of a vehicle dynamics model and control algorithm in real time, rendering engine to provide real-time visual representation of vehicle behavior and CAN communication to reduce networking load. It can provide also many different driving test environment and driving scenarios.